1. Field of the Invention
The disclosure relates generally to using data processing systems for sentiment analytics and, in particular, to managing improvements for sentiment analytics. Still more particularly, the present disclosure relates to using crowdsourcing to perform specified tasks associated with improving the effectiveness of sentiment analysis.
2. Description of the Related Art
Social media and Web 2.0 Technologies® have significantly enhanced interactive information sharing and collaboration over the Internet. Social networking sites, such as Facebook® and Twitter provide collaboration tools which allow users to interact with each other by exchanging messages with other computer users. Typical collaboration tools include tools for chatting, texting, instant messaging, multimedia messaging, emailing, conferencing, tweeting, and commenting.
Through the use of collaboration tools users sometimes express sentiments about features and aspects of entities. An entity is something that exists by itself, although it need not be of material existence. An entity is defined as a particular and discrete unit. For example, an entity may be a person, an organization, a thing, an abstract idea, a problem, a solution, and a particular type of activity. The entities discussed may be particularly named persons, places, or things and sometimes may include unnamed entities. An aspect of an entity is an appearance of the entity to the eye or mind. Some aspects of entities include physical appearances such as those based on sight, touch, smell, and other senses. Other aspects of entities include descriptions of metaphysical concepts, such as an aspect of a particular philosophy. More particularly, entities may have aspects that contrast one entity from other entities.
Sentiment of an aspect of an entity is a subjective expression of a positive, negative or neutral opinion of the aspect of the entity. For example, sentiment of an aspect of an entity may be defined on a scale such as between −5 to +5 with −5 being the most negative, +5 the most positive, and 0 as neutral.
Sentiment analytics refers to the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials. Using sentiment analytics, computer programs can mine source material to derive user sentiment about various aspects of entities. However, gaps may exist wherein the sentiment analysis of the source materials is determined to be insufficient to derive sentiment for some aspects of some entities.
Crowdsourcing is a process for performing certain kinds of tasks. In a crowdsourcing effort or procedure, a large group of organizations, individuals and other entities that desire to provide pertinent services, such as a specific community of providers or the general public, are invited to participate in a task that is presented by a task requester. At present, a crowdsourcing platform may serve as a broker or intermediary between the task requester and providers who are interested in undertaking or participating in task performance. Crowdsourcing platforms generally allow requesters to publish or broadcast their challenges and tasks, and further allow participating providers that are successful in completing the task to receive specified monetary rewards or other incentives. Innocentive®, TopCoder®, and MechanicalTurk® are examples of presently available platforms.
Currently however, there is no system or process available for creating and submitting crowdsourced tasks to address computer identified gaps in sentiment analysis of source materials determined to be insufficient to derive sentiment for aspects of entities.
Therefore, it would be advantageous to have a method, data processing system, and computer program product that takes into account at least some of the issues discussed above, as well as possibly other issues.
In one illustrative embodiment, a method, data processing system, and computer program product for managing analysis of sentiment is disclosed. A data processing system analyzes the data and the analysis of sentiment to determine if a gap exists requiring further processing to improve the analysis of sentiment. Responsive to a determination that the gap exists requiring further processing to improve the analysis of sentiment, the data processing system generates a task to address the gap. The data processing system then uses crowdsourcing to submit the generated task for processing.